COMPARISON OF ARGON PLASMA COAGULATION AND FORMALIN INSTILLATION IN THE TREATMENT OF RADIATION INDUCED HAEMORRHAGIC PROCTOCOLITIS

Background: Radiotherapy is routinely used in the treatment of pelvic malignancies and about 2–5% of these patients develop radiation-induced proctitis or proctocolitis. This complication of radiotherapy is treated in different ways. Two of these treatments, argon plasma coagulation (APC) and formalin instillation, have both been reported as to be successful modalities, but data comparing them are scarce. We conducted this study to compare these two treatment options. Methods: We reviewed the charts of patients who had radiation-induced proctocolitis and who were treated endoscopically at our tertiary care cancer centre with either APC or formalin instillation. Outcomes of the two treatments were compared in terms of bleeding control after the first session of treatment, the number of sessions required and the nal response to therapy. Results: Out of a total of 26 patients presenting with haemorrhagic radiation proctocolitis, 11 were treated with APC and 15 with formalin instillation. Success after the rst session was 53% in the formalin instillation group compared to 18% in the APC-treated group. On repeated sessions, the final response to both treatment modalities was comparable. Conclusion: Efficacy of APC and formalin instillation in the treatment of haemorrhagic radiation proctocolitis is comparable although formalin showed a better outcome after the first session. Key words: Argon plasma coagulation, formalin instillation, proctitis, radiation-induced colitis

Attenuation of hypotension using phenylephrine during induction of anaesthesia with propofol

Objective: To observe if phenylephrine mixed with propofol can attenuate hypotensive effects of propofol during induction of anaesthesia. Methods: A total number of 135 adult ASA-I and ASA-II patients were divided into three groups. (Group A, B and C). All patients were induced with propofol 2.5 mg per kg. In Group A (control group) patients received propofol mixed with 2cc of 0.9% normal saline. Group B (study group) patients received propofol mixed with 2cc of a solution containing phenylephrine 25µg/cc (total 50µg); Group C (study group) patients received propofol mixed with 2cc of a solution containing phenylephrine 50µg/cc (total 100µg). Haemodynamic variables like systolic, diastolic, mean arterial blood pressure and heart rate were noted. Hypotension was defined as 20% decrease in baseline systolic blood pressure recorded before induction of anaesthesia. Results: Phenylephrine in a dose of 100 micrograms attenuated the drop in systolic blood pressure. However phenylephrine in a dose 50 micrograms did not effectively prevent anticipated drop in SBP. Conclusion: Phenylephrine in doses of 100 micrograms effectively attenuates anticipated hypotension upon induction of general anaesthesia with propofo

Influence of single and multiple dry bands on critical flashover voltage of silicone rubber outdoor insulators: simulation and experimental study

Dry band formation on the surface of outdoor insulators is one of the main reasons leading to flashover and power outages. In this paper, a dynamic arc model is proposed for single and multiple dry bands configuration to predict the critical flashover voltage for silicone rubber outdoor insulators. An arc is modelled as a time dependent impedance consisting of a Resistor Inductor Capacitor (RLC) circuit. The effect of dry band location and existence of multiple dry bands on critical flashover voltage is investigated. To validate the proposed model, experiments were conducted in a climate chamber under controlled environmental conditions on rectangular silicone rubber sheets polluted using improved solid layer method based on IEC 60,507. Tests were conducted at different dry band configurations and pollution severity levels. A good correlation was found between experimental results and simulation results. This model can provide a good foundation for the development of mathematical models for station post insulators having multiple dry and clean bands and can be used in the design and selection of outdoor insulators for polluted conditions

Piezoelectric metamaterial with negative and zero Poisson's ratios

This study presents the finite element–based micromechanical modeling approach to obtain the electromechanical properties of the piezoelectric metamaterial based on honeycomb (HC) cellular networks. The symmetry of the periodic structure was employed to derive mixed boundary conditions (MBCs) analogous to periodic boundary conditions (PBCs). Three classes of hexagonal HC cellular networks, namely, a conventional HC (CHC), a re-entrant HC (RE), and a semi-re-entrant HC (SRE) were considered. The representative volume elements (RVEs) of these three classes of cellular materials were created, and finite element analyses were carried out to analyze the effect of orientation of the ligament on their effective electromechanical properties and their suitability in specific engineering applications. The longitudinally poled piezoelectric HC cellular networks showed an enhanced behavior as compared to the monolithic piezoelectric materials. Moreover, longitudinally poled HC cellular networks demonstrated that, as compared to the bulk constituent, their hydrostatic figure of merit increased and their acoustic impedance decreased by one order of magnitude, respectively, indicating their applicability for the design on hydrophones. Moreover, results showed that cellular metamaterial with tunable electromechanical characteristics and a variety of auxetic behaviors such as negative, positive, or zero Poisson’s ratios could be developed. Such novel HC network-based functional cellular materials are likely to facilitate the design of light-weight devices for various next-generation sensors and actuators

Fog computing enabled cost-effective distributed summarization of surveillance videos for smart cities

[EN] Fog computing is emerging an attractive paradigm for both academics and industry alike. Fog computing holds potential for new breeds of services and user experience. However, Fog computing is still nascent and requires strong groundwork to adopt as practically feasible, cost-effective, efficient and easily deployable alternate to currently ubiquitous cloud. Fog computing promises to introduce cloud-like services on local network while reducing the cost. In this paper, we present a novel resource efficient framework for distributed video summarization over a multi-region fog computing paradigm. The nodes of the Fog network is based on resource constrained device Raspberry Pi. Surveillance videos are distributed on different nodes and a summary is generated over the Fog network, which is periodically pushed to the cloud to reduce bandwidth consumption. Different realistic workload in the form of a surveillance videos are used to evaluate the proposed system. Experimental results suggest that even by using an extremely limited resource, single board computer, the proposed framework has very little overhead with good scalability over off-the-shelf costly cloud solutions, validating its effectiveness for IoT-assisted smart cities. (C) 2018 Elsevier Inc. All rights reserved.Nasir, M.; Muhammad, K.; Lloret, J.; Sangaiah, AK.; Sajjad, M. (2019). Fog computing enabled cost-effective distributed summarization of surveillance videos for smart cities. Journal of Parallel and Distributed Computing. 126:161-170. https://doi.org/10.1016/j.jpdc.2018.11.004S16117012

Instant dynamic response measurements for crack monitoring in metallic beams

This paper investigates the interdependencies of the modal behaviour of a cantilever beam, its dynamic response and crack growth. A methodology is proposed that can predict crack growth in a metallic beam using only its dynamic response. Analytical and numerical relationships are formulated between the fundamental mode and crack growth using the existing literature and finite element analysis (FEA) software, respectively. A relationship between the dynamic response and the modal behaviour is formulated empirically. All three relationships are used to predict crack growth and propagation. The load conditions are considered the same in all of the experiments for both model development and model validation. The predicted crack growth is compared with the visual observations. The overall error is within acceptable limits in all comparisons. The results obtained demonstrate the possibility of diagnosing crack growth in metallic beams at any instant within the operational conditions and environment

Energy, exergy and efficiency analysis of a flat plate solar collector used as air heater

Air heating by solar collectors is renewable technology providing hot air for different purposes. The present research emphasizes on analysis of energy, exergy and efficiency of a flat plate solar air heater. The analysis model was tested on five different air mass flow rates of 0.5 (Natural), 1.31, 2.11, 2.72 and 3.03 kgs-1 under three different tilt angles of 25, 35 (Recommended) and 50o. The data was replicated three times making a total of 45 treatments. A two factorial completely randomized design was used to find if there is any significant difference among the treatments. The results showed that the solar collector gave better performance at air mass flow of 3.03 kgs-1 under tilt of 35o. At maximum air mass flow rate of 3.03 kgs-1and optimum tilt angle of 35o the maximum energetic efficiency of 51%, while minimum exergetic efficiency of 24% and maximum overall efficiency of 71% were recorded. It was concluded that to get maximum thermal efficiencies of 71% from flat plate solar collector used as an air heater must be operated at high air mass flow rates of 3.03 kgs-1under 35o tilt angle at Peshawar, Pakistan

Personality factors and burnout among medical students and house officers

Objective: To determine the personality factors relevance with the burn out among health professionals.Methodology: The cross-sectional study was conducted government medical colleges and hospitals of Lahore, from Feb 2017 to Nov 2017.  Participants were selected through purposive sampling assessment of burnout. The abbreviated nine items inventory “abbreviated Maslach Burnout Inventory (aMBI) was used and the short form of “Zukerman Kuhlman Personality Questionnaire” (ZKPQ) was used to assess the personality characteristics of participants. “Regression Analysis” was used for assessment of predictive relationship between personality and burnout.Results: A total of 240 participants were included. Two personality factors Neuroticism-anxiety (N-anx) and Activity (Act) appeared as significant predictor of “Emotional Exhaustion” among house officers and final year medical students (p<.001) and other personality factors of Impulsive sensation seeking (ImpSS), Aggression-hostility (Agg-host), and Sociability (Sy) showed non-significant relationship with “Emotional Exhaustion”. Neuroticism-anxiety (N-Anx) appears as significant predictor of “Depersonalization” among house officers and final year medical students (p<.00)1, Activity (Act) appears as significant predictor of “Personal Accomplishment” among house officers and final year medical students (p <.003).Conclusion: Combination of high neuroticism-anxiety and high activity are the predicting personality factors for burnout

Short-Term Load Forecasting Using AMI Data

Accurate short-term load forecasting is essential for efficient operation of the power sector. Predicting load at a fine granularity such as individual households or buildings is challenging due to higher volatility and uncertainty in the load. In aggregate loads such as at grids level, the inherent stochasticity and fluctuations are averaged-out, the problem becomes substantially easier. We propose an approach for short-term load forecasting at individual consumers (households) level, called Forecasting using Matrix Factorization (FMF). FMF does not use any consumers' demographic or activity patterns information. Therefore, it can be applied to any locality with the readily available smart meters and weather data. We perform extensive experiments on three benchmark datasets and demonstrate that FMF significantly outperforms the computationally expensive state-of-the-art methods for this problem. We achieve up to 26.5% and 24.4 % improvement in RMSE over Regression Tree and Support Vector Machine, respectively and up to 36% and 73.2% improvement in MAPE over Random Forest and Long Short-Term Memory neural network, respectively